Three-dimensional (3D) body scanning technology has shown the potential of providing data that can be used to improve the fit of clothing. 3D body scanners can automatically generate a set of over 100 measurements in a short time (5 to 15 seconds for the scan, 1 to 2 minutes to generate measurements), and therefore they have been used for several large-scale anthropometric surveys in the U.K., the U.S., Germany, Japan, Korea, and Thailand. Up-to-date anthropometric data assists ready-to-wear apparel companies to identify sectors of the market, and update their sizing systems to provide good fit for their target market customers. Mass customization and automated custom clothing have recently been regarded as an additional way for the apparel industry to address consumer complaints about garment fit; 3D body scanners are useful tools in implementing these processes. Apparel companies such as Brooks Brothers, Lori Coulter, and C&A have produced custom-made garments using measurements taken from a 3D body scanner. By providing fit that is individualized on the basis of the customer's objective body measurements, these apparel companies provide improved fit for each customer.
Other apparel companies have created online custom clothing services by having the customer self-report his or her measurements. Archetype Solutions is a representative service provider for online made-to-measure apparel companies. They have developed a simple and intuitive ordering process that allows the consumer to order a garment based on their self-measurements, perceived body shapes, and style preferences in a few minutes over the internet. JCPenney, Land's End, QVC, and indiDenim have utilized similar ordering processes for women/men's Chino pants or jeans, or men's dress shirts.
In the apparel industry, body type, sometimes referred to as “body shape,” has increasingly been recognized as a fundamental factor to a good fit. Apparel companies such as Gap Inc. and The Limited provide ‘Straight’ and ‘Curvy’ pants styles for customers with different lower body types. Zafu is an online size selection company which offers recommendations on which jeans are likely to fit the user best among 90 denim brands on the basis of a user's body shape and previous fit problems with their jeans. Zafu spent over six years researching and understanding body types, tested hundreds of pairs of jeans on 11,500 women, and developed a ‘shape matching’ technology. They found that women with identical hip measurements can have totally different body types, resulting in different fit problems. Only 6% of women have the same body type as the typical tall and slim fit model, but the problem is that most jeans companies consider these women ‘average’. Zafu claims that their body type-based recommendations make it possible for 94% of 5,872,964 users to find their “perfect” jeans, but online return rates of apparel merchandise are generally about 50%.
Body type is also recognized to be a factor in creating custom-fit solutions. Staples was the first researcher in the U.S. to create different patterns designed for different body types for base block patterns while developing U.S. army men's dress uniforms in 2000. In Archytype's custom ordering process, customers are asked to specify their own body type from pictures of basic silhouettes and a text description in addition to their self-reported measurements. Automated made-to-measure computer-aided design programs (e.g., AccuMark MTM of Gerber Scientific, FitNet of Lectra Systems, and MtM.assyst of Assyst GmbH), may also benefit from use of body type information Simmons, Istook, and Devarajan felt that customization could be improved if it started from the most correctly shaped garment for each customer's body type. Ashdown and Dunne noted that the accuracy of body chart data, reliability of body measurement data, and fit preferences are critical elements in a system designed to automate patternmaking (Ashdown, S. P., and Dunne, L., A Study of Automated Custom Fit: Readiness of the Technology for the Apparel Industry, Clothing Textiles Res. J. 24(2), 121-136 (2006)). However, even after three iterative corrections of all these issues, these researchers found that only seven of ten custom-made garments from the system provided good fit. This limitation of automated custom system was also observed previously by the inventors when they worked with two large sportswear companies to develop automated custom-made systems for jacket and pant styles. Existing systems could not generate custom-made patterns with consistent good fit for these garments even after corrections of all issues enumerated in Ashdown and Dunne's study. In the custom jacket studies, when the hip girth was determined as a primary measurement for initiating the custom fit process, the fit at the bust was poor although the fit at the hip was appropriate. In contrast, when the bust girth was set as a primary measurement, the fit at the bust was appropriate, but the fit at the hip was not good. The custom-made clothing had especially poor fit for those people with a body type different from that of the fit model for the base pattern, resulting in a different silhouette, since this situation created the need for an extreme pattern alteration in a specific area.
Citation or identification of any reference in Section 2, or in any other section of this application, shall not be considered an admission that such reference is available as prior art to the present invention.